Ice cream sales are notoriously dependent on weather conditions. Six years ago De IJsMaker was established in Rotterdam to address the need for reasonably priced, superior ice cream. The brand is currently growing quickly and intends to go national. This success is primarily attributable to creative digital transformation and data-driven decision-making, using digital tools to streamline operations.
As it expanded, De IJsMaker ran into operational difficulties. In order to optimize staffing and inventory, the owner used the Cohelion Data Platform to analyze sales, weather forecasts, and local events. employing digital business models, where increasing customer satisfaction and efficiency is greatly aided by data analytics. To ensure they have the right inventory and personnel on hand, their Flavor Predictor tool, for example, uses weather and historical data to forecast which flavors will sell best on a particular day.
Even though De IJsMaker makes good use of data analytics, ice cream shops could benefit even more from the integration of AI and machine learning. To produce even more accurate forecasts, AI might examine more complex data patterns, such as social media trends and consumer behavior. This use of AI is related to the value that businesses can derive from information goods. AI might, for instance, improve dynamic pricing, provide promotions based on demand in real time, or make tailored flavor recommendations at shops to improve the user experience. Furthermore, research has demonstrated that conversational AI like chatbots for online ordering and reservations can greatly increase both operational effectiveness and customer satisfaction.
Expanding into AI does however come with challenges. It requires significant investment and technical expertise. However, as seen with their self-service kiosks, even incremental changes can greatly improve efficiency and sales. The potential for AI to further personalize and streamline operations is promising, but it needs careful implementation.
In my opinion the IJsMaker’s journey highlights the power of data in transforming a small business. The potential for AI in this context is exciting, offering a way to enhance customer experiences and operational efficiency. However, it raises questions about the balance between investment and return, especially for smaller businesses. Could the integration of AI in small businesses like De IJsMaker be a feasible and beneficial step? How might customers feel about their buying patterns being used to enhance their experience?
References:
Conversational AI in Restaurants Case Study: How AI Is Transforming the Dining Experience. (2023, November 29). Pragmatic. https://www.pragmatic.digital/blog/conversational-ai-in-restaurants-case-study-how-ai-is-transforming-the-dining-experience
Gawkowski, E. (2024, July 8). AI in Restaurants: 10 Tips on How to Boost Your Restaurant with AI | UpMenu. UpMenu. https://www.upmenu.com/blog/ai-restaurant/
Suurenbroek, H. (2024, July 2). Read De IJsmaker case study and learn what they gained. Cohelion • Data Management and Integration Platform. https://cohelion.com/other-industries/de-ijsmaker/
